Predicting chronic kidney disease after cisplatin treatment using population-level data

Importance — Cisplatin is a widely used treatment for cancer that can permanently damage the kidneys. Treatment modifications and other strategies may prevent chronic kidney disease (CKD) in patients at risk; however, the incidence and predictability of CKD following cisplatin treatment remain poorly understood.

Objective — To characterize the incidence of CKD after cisplatin treatment and evaluate prediction models.

Design, setting, and participants — In this population-based prognostic study, prediction models were developed based on a retrospective cohort study of patients who received cisplatin chemotherapy for nonhematologic cancer in an outpatient setting between July 1, 2014, and June 30, 2017. Models were tested on a temporal-test cohort of patients from Ontario, Canada, who started treatment between July 1, 2017, and June 30, 2020, and an external-test cohort of patients from a single center in the United States. Data were analyzed from May 1, 2021 to May 7, 2025.

Exposures — Predictive features included demographics, cancer diagnosis, cisplatin dose and schedule, comorbidities, laboratory testing, and patient-reported symptoms.

Main outcomes and measures —The outcomes were CKD (estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m2) and the eGFR after cisplatin treatment. Measures included the area under the receiver operating characteristic curve and the mean absolute error (MAE).

Results — The population-level cohort included 9521 patients (median age, 63 years [IQR, 56-70 years]; 4841 men [50.8%]). Among the 9010 patients without pretreatment CKD, 1228 (13.6%) developed CKD, 81 (0.9%) developed grade 4 or worse CKD, and 16 (0.18%) required dialysis. The eGFR decreased by a mean of 8.1 mL/min/1.73 m2 (95% CI, 7.8-8.4 mL/min/1.73 m2). A simple spline-based regression model based solely on the pretreatment eGFR predicted posttreatment CKD in the temporal-test cohort (area under the curve, 0.80 [95% CI, 0.78-0.82]) and the external-test cohort (area under the curve, 0.73 [95% CI, 0.66-0.78]). Similarly, the posttreatment eGFR was predicted by a spline regression based solely on the pretreatment eGFR (temporal-test MAE, 12.6 mL/min/1.73 m2 [95% CI, 12.3-13.0 mL/min/1.73 m2]; external-test MAE, 14.3 mL/min/1.73 m2 [95% CI, 13.2-15.5 mL/min/1.73 m2]). Complex machine learning systems incorporating all features failed to improve predictions over the univariable models.

Conclusions and relevance — This study found that cisplatin treatment was followed by a predictable decrease in the eGFR, placing patients with a lower baseline eGFR at the highest risk of CKD. A simple model based on the pretreatment eGFR predicts CKD risk and could guide clinical decision-making.